Sync from v0.13

tests/quantization/test_experts_int8.py

@@ -0,0 +1,39 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+# flake8: noqa
+"""Tests experts_int8 quantization startup and generation,
+doesn't test correctness
+"""
+
+import pytest
+
+from tests.quantization.utils import is_quant_method_supported
+
+from ..models.registry import HF_EXAMPLE_MODELS
+
+MODELS = ["ai21labs/Jamba-tiny-random", "pfnet/plamo-2-1b"]
+
+
+@pytest.mark.skipif(
+    not is_quant_method_supported("experts_int8"),
+    reason="ExpertsInt8 is not supported on this GPU type.",
+)
+@pytest.mark.parametrize("model", MODELS)
+@pytest.mark.parametrize("dtype", ["bfloat16"])
+@pytest.mark.parametrize("max_tokens", [4])
+def test_model_experts_int8_startup(
+    hf_runner,
+    vllm_runner,
+    example_prompts,
+    model: str,
+    dtype: str,
+    max_tokens: int,
+) -> None:
+    model_info = HF_EXAMPLE_MODELS.find_hf_info(model)
+    model_info.check_transformers_version(on_fail="skip")
+
+    with vllm_runner(
+        model, dtype=dtype, enforce_eager=True, quantization="experts_int8"
+    ) as vllm_model:
+        vllm_model.generate_greedy(example_prompts, max_tokens)